7 papers · 1 filter
Active Learning for Cascaded Object Detection: Balancing Coverage and Uncertainty in Table Extraction Pipelines
Eliott Thomas, Mickael Coustaty, Aurelie Joseph +3
Table extraction from business documents relies on a cascaded pipeline where Table Detection (TD) first localizes tables and Table Structure Recognition (TSR) then recovers their i…
ConRTF: Edge-Constrained Boundary Distribution Refinement for Realtime TransFormer Table Structure Recognition
Eliott Thomas, Tri-Cong Pham, Mickael Coustaty +5
Table Structure Recognition (TSR) aims to recover the row and column layout of tables from document images, a key step in document understanding pipelines. Accurate TSR depends on…
DocQT: Improving Document Forgery Localization Robustness via Diverse JPEG Quantization Tables
Kylian Ronfleux-Corail, Guillaume Bernard, Mickaël Coustaty +3
Document manipulation localization models achieve strong performance on public benchmarks yet fail to generalize to operational document workflows. We identify a critical and overl…
Evaluating the Impact of Khmer Font Types on Text Recognition
Vannkinh Nom, Souhail Bakkali, Muhammad Muzzamil Luqman +2
Text recognition is significantly influenced by font types, especially for complex scripts like Khmer. The variety of Khmer fonts, each with its unique character structure, present…
RAPTOR: Refined Approach for Product Table Object Recognition
Eliott Thomas, Mickael Coustaty, Aurelie Joseph +4
Extracting tables from documents is a critical task across various industries, especially on business documents like invoices and reports. Existing systems based on DEtection TRans…
KhmerST: A Low-Resource Khmer Scene Text Detection and Recognition Benchmark
Vannkinh Nom, Souhail Bakkali, Muhammad Muzzamil Luqman +2
Developing effective scene text detection and recognition models hinges on extensive training data, which can be both laborious and costly to obtain, especially for low-resourced l…